search for: dbinom

...nvestigate further) led me to take a close look at the code for binom.test(). I now have a query! The code for the two-sided case computes the p-value as follows: if (p == 0) (x == 0) else if (p == 1) (x == n) else { relErr <- 1 + 1e-07 d <- dbinom(x, n, p) m <- n * p if (x == m) 1 else ## PVAL if x < m if (x < m) { i <- seq(from = ceiling(m), to = n) y <- sum(dbinom(i, n, p) <= d * relErr) ## here: pbinom(x,n,p) + pbinom(n-y,n,p,lower=FA...

Hello, I want to estimate the parameters of a binomial distributed rv using MLE. Other distributions will follow. The equation system to solve is not very complex, but I've never done such work in R and don't have any idea how to start... The system is: (1) n*P = X (2) [sum {from j=0 to J-1} Y{j} /(n-j)] = -n * ln (1-X / n) where * only X is given (empirical mean)

Hi Folks, There has been past correspondence regarding Catherine Loader's Bell Labs (oops, Lucent) paper "Fast and Accurate Computation of Binomial Probabilities" which gives the algorithm on which R's dbinom() is based. The original URL given in the R documentation "?dbinom" is: http://cm.bell-labs.com/cm/ms/departments/sia/catherine/dbinom but this link is dead. Likewise, Marc Schwarz (in reply to Aries Arditi on Thu Dec 11 2003) gives http://kiefer.stat.cwru.edu/~catherine/pubs.html...

Hi Guy's I was wondering if someone could point me in the right direction. dbinom(10,1,0.25) I am using dbinom(10,1,0.25) to calculate the probabilty of 10 judges choosing a certain brand x times. I was wondering how I would go about simulating 1000 trials of each x value ? regards Brendan -- View this message in context: http://www.nabble.com/Binomial-simulation-tp2310634...

...pply(0:m1,function(x1) >>>>do.call(rbind,lapply(0:n1,function(y1) >>>>expand.grid(m1,n1,x1,y1)))))))))? >>>>names(d)<-c("m1","n1","x1","y1") >>>> >>>>d<-within(d,{ >>>>term1_p1<- dbinom(x1,m1, p1L, log=FALSE)* dbinom(y1,n1,p1H, log=FALSE) >>>>term1_p0<- dbinom(x1,m1, p0L, log=FALSE)* dbinom(y1,n1,p0H, log=FALSE) >>>>}) ? ? ? >>>> >>>>########## add Qm Qn ################################## >>>>set.seed(8) >>>&g...

Hi all Is there any reason why the parameter i in a "for" loop ignores a value of zero? For example sim=c() p=.2 for(i in 0:5) {sim[i]=dbinom(i,5,p) } sim [1] 0.40960 0.20480 0.05120 0.00640 0.00032 In this example the quantile i= 0 was ignored since dbinom(0,5,p) [1] 0.32768 The same behaviour occurs if I use a while loop to perform the same calculation: sim=c() p=.2 i=0 while(i <6) {sim[i]=dbinom(i,5,p) i=i+1 } sim [1]...

Full_Name: Chanseok Park Version: R 2.2.1 OS: RedHat EL4 Submission from: (NULL) (130.127.112.89) pbinom(any negative value, size, prob) should be zero. But I got the following results. I mean, if a negative value is close to zero, then pbinom() calculate pbinom(0, size, prob). dbinom() also behaves similarly. > pbinom( -2.220446e-22, 3,.1) [1] 0.729 > pbinom( -2.220446e-8, 3,.1) [1] 0.729 > pbinom( -2.220446e-7, 3,.1) [1] 0

...and that the author has > significant published works which are open access, I'd be surprised if > there's any objection to reproducing it. > > > On Mon, May 18, 2020 at 8:01 PM Koenker, Roger W <rkoenker at illinois.edu> wrote: >> >> FWIW the link from ?dbinom to the Loader paper on Binomials is broken but the paper seems to be >> available here: https://octave.1599824.n4.nabble.com/attachment/3829107/0/loader2000Fast.pdf >> >> Roger Koenker >> r.koenker at ucl.ac.uk<mailto:r.koenker at ucl.ac.uk> >> Honorary Profes...

FWIW the link from ?dbinom to the Loader paper on Binomials is broken but the paper seems to be available here: https://octave.1599824.n4.nabble.com/attachment/3829107/0/loader2000Fast.pdf Roger Koenker r.koenker at ucl.ac.uk<mailto:r.koenker at ucl.ac.uk> Honorary Professor of Economics Department of Economics, UCL...

What about using the Wayback Machine archive ? The web archive should be more stable than other links which also might disappear in the future. E.g. https://web.archive.org/web/20070610002602/http://www.herine.net/stat/software/dbinom.html , which also links to an archived copy of the PDF. Best regards, Hilmar On 18.05.20 10:57, peter dalgaard wrote: > In principle a good idea, but I'm not sure the whereabouts of Catherine Loader are known at this point. Last peeps from her on the net seem to be about a decade old. &g...

I'm trying to fathom how to answer two example problems (3.3.2 & 3.3.3) in: Krishnamoorthy. 2006. "handbook of statistical distributions with applications" The first requires calculating single trial probability of success for a binomial distribution when we know: trial size=20, successes k=4, P(x<=k)=0.7 Appreciably all the binomial functions are requiring "prob",

...t restrictions on reproducing it), and that the author has significant published works which are open access, I'd be surprised if there's any objection to reproducing it. On Mon, May 18, 2020 at 8:01 PM Koenker, Roger W <rkoenker at illinois.edu> wrote: > > FWIW the link from ?dbinom to the Loader paper on Binomials is broken but the paper seems to be > available here: https://octave.1599824.n4.nabble.com/attachment/3829107/0/loader2000Fast.pdf > > Roger Koenker > r.koenker at ucl.ac.uk<mailto:r.koenker at ucl.ac.uk> > Honorary Professor of Economics >...

...density plot in that http://en.wikipedia.org/wiki/File:Binomial_distribution_pmf.svg wiki page ? and the cumalative plot as well? ==================================== # Binomial Distribution x=0:40 plot(sin,ylim=c(0,.20),xlim=c(0,40),type='n',xlab="n",ylab="") points(dbinom(x,20,0.5)) points(dbinom(x,20,0.7),col=2) points(dbinom(x,40,0.5),col=3) ==================================== Thanks. -- View this message in context: http://n4.nabble.com/how-do-I-get-the-legend-tp1563309p1563309.html Sent from the R help mailing list archive at Nabble.com.

...ook and SAS both show 2*9.94e-07 = 1.988e-06 as the two tailed value. As does the R summation syntax from R below. It looks to me like the alternative hypothesis language should be revised to something like " ... greater than or equal to ..." Am I mistaken? M.C.Grant > 2*sum(dbinom(c(10:25),25,0.061)) [1] 1.987976e-06 > binom.test(10,25,0.061) Exact binomial test data: 10 and 25 number of successes = 10, number of trials = 25, p-value = 9.94e-07 alternative hypothesis: true probability of success is not equal to 0.061 95 percent confidence interv...

...+ lik<-function(parms){ + r<-expit(parms[1]) + lambda<-exp(parms[2]) + pvec<-1-(1-r)^(0:Nmax) + gN<-dpois(0:Nmax,lambda) + gN<-gN/sum(gN) + lik<-rep(NA,nsites) + for(i in 1:nsites){ + lik[i]<-sum(dbinom(y[i],J,pvec)*gN) + } + -1*sum(log(lik)) + } + #### + + tmp<-nlm(lik,c(0,0),hessian=TRUE) + ests<-tmp$estimate + aic<-tmp$minimum*2 + 2*length(ests) + se<- sqrt(diag(solve(tmp$hessian))) + list(ests=ests,se=se,aic=aic) + } but when I try to see t...

...ollowing Sweave minimal file: ---<--------------------cut here---------------start------------------->--- \documentclass{article} \usepackage{Sweave} \begin{document} <<binom-sim>>= thetas <- seq(0, 1, by=0.001) prior <- rep(1, length(thetas)) / length(thetas) lik <- dbinom(1, 1, thetas) lik.p <- prior * lik post <- lik.p / sum(lik.p) <<binom-sim-fig, fig=TRUE, include=FALSE, height=3, echo=FALSE>>= layout(matrix(1:2, ncol=2)); par(mar=c(5, 4, 2, 1), cex=0.75) matplot(thetas, cbind(prior, lik, post), type="l", lty=c(2, 1, 1), xlab=...

...0.50 0.55 0.60 0.65 0.70 [16] 0.75 0.80 0.85 0.90 0.95 1.00 > > > > cleanEx(); ..nameEx <- "Binomial" > > ### * Binomial > > flush(stderr()); flush(stdout()) > > ### Name: Binomial > ### Title: The Binomial Distribution > ### Aliases: Binomial dbinom pbinom qbinom rbinom > ### Keywords: distribution > > ### ** Examples > > # Compute P(45 < X < 55) for X Binomial(100,0.5) > sum(dbinom(46:54, 100, 0.5)) [1] 0.6317984 > > ## Using "log = TRUE" for an extended range : > n <- 2000 > k <- seq(0,...

Thank you very much for your reply. Your code work well with this example. I modified a little to fit my real data, I got an error massage. Error in split.default(x = seq_len(nrow(x)), f = f, drop = drop, ...) : Group length is 0 but data length > 0 On Thu, Jan 31, 2013 at 12:21 PM, arun kirshna [via R] < ml-node+s789695n4657196h87@n4.nabble.com> wrote: > Hi, > Try this: >

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Hi all, I have some problems with the mle2 function > RogersIIbinom <- function(N0,attackR3_B,Th3_B) {N0-lambertW(attackR3_B*Th3_B*N0*exp(-attackR3_B*(24-Th3_B*N0)))/(attackR3_B*Th3_B)} > RogersII_B <- mle2(FR~dbinom(size=N0,prob=RogersIIbinom(N0,attackR3_B,Th3_B)/N0),start=list(attackR3_B=1.5,Th3_B=0.04),method="Nelder-Mead",data=dat) Error in dbinom(x, size, prob, log) : Non-numeric argument to mathematical function Can somenone explain met what this error means? All my parameters and data are...